Exploring the Health Literacy Behavior Patterns of Male Patients Using an Interpretable Method.

Background: Improving overall and individual health literacy is a major focus of national initiatives in China and similar initiatives globally. However, few studies have examined the identification and improvement of individual health literacy levels, especially among patients. Purpose: To develop an interpretable method with decision rules to assess the health literacy levels of male patients and identify key factors influencing health literacy levels. Methods: Using a convenience sampling method, we conducted on-site surveys with 212 male patients of a hospital in China from July 2020 to September 2020. The questionnaire was developed by the Ministry of Health of the People's Republic of China. A total of 206 of the completed surveys were ultimately included for analyses in this study. The rough set theory was used to identify conditional attributes (ie, key factors) and decision attributes (ie, levels of health literacy) and to establish decision rules between them. These rules specifically describe how different combinations of conditional attributes can affect health literacy levels among men. Results: Basic knowledge, concepts, and health skills are important in identifying whether male patients have health literacy. Health skills, scientific health concepts, healthy lifestyles and behaviors, infectious disease prevention and control literacy, basic medical literacy, and health information literacy can be identified as cognitive behaviors with varying degrees of health literacy among patients. Conclusion: This model can effectively identify the key factors and decision rules for male patients' health literacy. Simultaneously, it can be applied to clinical nursing practice, making it easier for hospitals to guide male patients to improve their health literacy.

Identification of key risk factors for venous thromboembolism in urological inpatients based on the Caprini scale and interpretable machine learning methods.

PURPOSE: To identify the key risk factors for venous thromboembolism (VTE) in urological inpatients based on the Caprini scale using an interpretable machine learning method. METHODS: VTE risk data of urological inpatients were obtained based on the Caprini scale in the case hospital. Based on the data, the Boruta method was used to further select the key variables from the 37 variables in the Caprini scale. Furthermore, decision rules corresponding to each risk level were generated using the rough set (RS) method. Finally, random forest (RF), support vector machine (SVM), and backpropagation artificial neural network (BPANN) were used to verify the data accuracy and were compared with the RS method. RESULTS: Following the screening, the key risk factors for VTE in urology were "(C1) Age," "(C2) Minor Surgery planned," "(C3) Obesity (BMI > 25)," "(C8) Varicose veins," "(C9) Sepsis (< 1 month)," (C10) "Serious lung disease incl. pneumonia (< 1month) " (C11) COPD," "(C16) Other risk," "(C18) Major surgery (> 45 min)," "(C19) Laparoscopic surgery (> 45 min)," "(C20) Patient confined to bed (> 72 h)," "(C18) Malignancy (present or previous)," "(C23) Central venous access," "(C31) History of DVT/PE," "(C32) Other congenital or acquired thrombophilia," and "(C34) Stroke (< 1 month." According to the decision rules of different risk levels obtained using the RS method, "(C1) Age," "(C18) Major surgery (> 45 minutes)," and "(C21) Malignancy (present or previous)" were the main factors influencing mid- and high-risk levels, and some suggestions on VTE prevention were indicated based on these three factors. The average accuracies of the RS, RF, SVM, and BPANN models were 79.5%, 87.9%, 92.6%, and 97.2%, respectively. In addition, BPANN had the highest accuracy, recall, F1-score, and precision. CONCLUSIONS: The RS model achieved poorer accuracy than the other three common machine learning models. However, the RS model provides strong interpretability and allows for the identification of high-risk factors and decision rules influencing high-risk assessments of VTE in urology. This transparency is very important for clinicians in the risk assessment process.

Psychological resilience factors in intensive care nursing: a hybrid multi-criteria decision-making model.

PURPOSE: To analyze the key factors influencing the psychological resilience of intensive care unit (ICU) nurses during the COVID-19 pandemic and put forward suggestions promoting resilience based on key improvement factors and clinical experience. METHODS: Data were collected from 35 ICU nurses in a hospital in Zhejiang Province, China, through a questionnaire survey conducted between January and February 2023. The Decision-Making Trial and Evaluation Laboratory (DEMATEL) method was then used to construct and visualize the relationship structure between the factors. The DEMATEL-based Analytical Network Process (DANP) was applied to determine the influential weights of all factors. Finally, the key improvement factors were identified using importance-performance analysis (IPA). RESULTS: Based on the cause-effect impact network diagram (CEIND), it was concluded that (C 11), (C 22), and (C 32) are the key factors that promote the improvement of psychological resilience among ICU nurses. Additionally, these factors were the key factors that influence psychological resilience. The confidence levels of these results and the gap were 99.6% and 0.4%, respectively, which exceed the threshold value of 95%, indicating good stability. Finally, for the case hospitals, (C 13) was identified as the key improvement factor. CONCLUSIONS: Hospital administrators should support ICU nurses in enhancing their psychological resilience during major epidemics by: (i) Providing training on comprehensive protective measures and nursing skills; (ii) Effectively managing the human resources of nurses in the hospital to reduce their workload; (iii) Increasing social and organizational support for nurses to alleviate anxiety caused by large-scale public health events and improve their psychological resilience.

Improving the academic resilience of hospital nursing interns through a hybrid multi-criteria decision analysis model.

Purpose: To identify the main variables affecting the academic adaptability of hospital nursing interns and key areas for improvement in preparing for future unpredictable epidemics. Methods: The importance of academic resilience-related variables for all nursing interns was analyzed using the random forest method, and key variables were further identified. An importance-performance analysis was used to identify the key improvement gaps regarding the academic resilience of nursing interns in the case hospital. Results: The random forest showed that five items related to cooperation, motivation, confidence, communication, and difficulty with coping were the main variables impacting the academic resilience of nursing interns. Moreover, the importance-performance analysis revealed that three items regarding options examination, communication, and confidence were the key improvement areas for participating nursing interns in the case hospital. Conclusions: For the prevention and control of future unpredictable pandemics, hospital nursing departments can strengthen the link between interns, nurses, and physicians and promote their cooperation and communication during clinical practice. At the same time, an application can be created considering the results of this study and combined with machine learning methods for more in-depth research. These will improve the academic resilience of nursing interns during the routine management of pandemics within hospitals.

Chinese Health Insurance in the Digital Era: Bibliometric Study.

BACKGROUND: China has entered the era of digital health care after years of reforms in the health care system. The use of digital technologies in healthcare services is rapidly increasing, indicating the onset of a new period. The reform of health insurance has also entered a new phase. OBJECTIVE: This study aims to investigate the evolution of health care insurance within the context of telemedicine and Internet Plus Healthcare (IPHC) during the digital health care era by using scientometric methods to analyze publication patterns, influential keywords, and research hot spots. It seeks to understand how health care insurance has adapted to the growing integration of IPHC and telemedicine in health care services and the implications for policy and practice. METHODS: A total of 411 high-quality studies were curated from the China National Knowledge Infrastructure (CNKI) database in the Chinese language, scientometric analysis was conducted, and VOSviewer software was used to conduct a visualized analysis of keywords and hot spots in the literature. RESULTS: The number of articles in this field has increased notably from 2000 to 2022 and has increased annually based on a curve of y=0.332exp (0.4002x) with R2=0.6788. In total, 62 institutions and 811 authors have published research articles in the Chinese language in this field. This study included 290 keywords and formulated a total of 5 hot-topic clusters of "telemedicine," "IPHC," "internet hospital," "health insurance payments," and "health insurance system." CONCLUSIONS: Studies on the application of digital technologies in health care insurance has evolved from foundational studies to a broader scope. The emergence of internet hospitals has showcased the potential for integrating IPHC services into insurance payment systems. However, this development also highlights the necessity for enhanced interregional coordination mechanisms. The reform of health insurance payment is contingent upon ongoing advancements in digital technology and increased investment in electronic medical records and primary health care services. Future efforts should focus on integrating technology with administrative systems, advancing mobile health care solutions, and ensuring interoperability among various payment systems to improve efficiency and standardize health care services.

Improve the satisfaction of medical staff on the use of home nursing mobile APP by using a hybrid multi-standard decision model.

OBJECTIVE: To identify critical satisfaction gaps in a home nursing mobile application (APP) using a systematic decision-making model. METHODS: Initially, the decision-making trial and evaluation laboratory method was used to analyze the relationship structure and corresponding weights among the indicators. The Importance-Performance Analysis (IPA) method was used to identify the categories of all indicators and their corresponding strategic directions. Twenty-six home nursing specialists currently providing home nursing services were recruited for this study. RESULTS: The IPA results revealed that "Assurance," "Reliability," and "Personal security protection" are critical satisfaction gaps. From the influence network and weight results, "information quality" and "system quality" were the critical quality factors in the home nursing mobile APP. The influence of the network relationship structure and weight demonstrated a 98.12% significance level, indicating good stability. CONCLUSION: Continuous improvement in information and system quality is recommended to optimize the overall quality of the home nursing mobile APP. Additionally, user demands should be considered, and personal safety guarantee functions should be developed and integrated into the system to ensure the safety of home nursing workers.

Hydroxy-Functionalized Ionic Liquids under Pressure: The Influence on Hydrogen Bonding between Ions of Opposite and Like Charges.

Hydroxy functionalization of cations in ionic liquids (ILs) can lead to formation of hydrogen bonds between their OH groups, resulting in so-called (c-c) H-bonds. Thereby, the (c-c) H-bonds compete with regular H-bonds (c-a) between the OH groups and the anions. Polarizable cations, weakly interacting anions, and long alkyl chains at the cation support the propensity for the formation of (c-c) H-bonds. At low temperatures, the equilibrium between (c-c) and (c-a) H-bonds is strongly shifted in favor of the cation-cation interaction. Herein, we clarify the pressure dependence on (c-c) and (c-a) H-bond distributions in the IL 1-(2-hydroxyethyl)-3-methylimidazolium hexafluorophosphate [HOC2C1Im][PF6], in mixtures of [HOC2C1Im][PF6] with the nonhydroxy-functionalized IL 1-propyl-3-methylimidazolium hexafluorophosphate [C3C1Im][PF6] and in [HOC2C1Im][PF6] including trace amounts of water. The infrared (IR) spectra provide clear evidence that the (c-c) H-bonds diminish with increasing pressure in favor of the (c-a) H-bonds. Adding trace amounts of water results in enhanced (c-c) clustering due to cooperative effects. At ambient pressure, the water molecules are involved in the (c-c) H-bond motifs. Increasing pressure leads to squeezing them out of H-bond clusters, finally resulting in demixing of water and the IL at the microscopic level.

Identifying key mental health and improvement factors in hospital administrators working from home using a DEMATEL-based network analysis model.

Purpose: To identify the key mental health and improvement factors in hospital administrators working from home during COVID-19 normalization prevention and control. Methods: The survey was conducted from May to June 2023, and the practical experiences of 33 hospital administrators were collected using purposive sampling. The study examined a set of mental health factor systems. The relationship structure between the factors was constructed using the Decision-making Trial and Evaluation Laboratory (DEMATEL) method. Finally, the structure was transformed using the influence weight of each factor via the DEMATEL-based Analytic Network Process. Results: Regarding influence weight, the key mental health factors of hospital administrators are mainly "lack of coordination," "time management issues," and "work-life imbalances." The influential network relation map shows that improvements can be made by addressing "improper guidelines," "laziness due to being at home," and "job insecurity" because they are the main sources of influence. The reliability level of the results for the network structure and weight was 98.79% (i.e., the gap was 1.12% < 5%). Conclusion: The network analysis model based on DEMATEL proposed in this study can evaluate the mental health factors of hospital administrators during the pandemic period from a multidimensional and multidirectional perspective and may help improve mental health problems and provide suggestions for hospital administrators.

Identification of key potential risk areas and key potential failure modes in hemodialysis rooms by the FMEA method following routine prevention and control of the COVID-19 pandemic.

Hemodialysis is an important part of nosocomial infection prevention and control (IPC). This study aimed to identify the key potential risk areas and failure modes in hemodialysis rooms in hospitals and put forward a series of improvement measures to prevent and control the spread of the coronavirus disease 2019 (COVID-19). Hemodialysis patients are highly susceptible to COVID-19 and usually have a high incidence of severe illness and mortality after infection with COVID-19. Therefore, IPC in hemodialysis patients is of crucial strategic significance. Based on 30 domain experts' interviews and careful analysis of prevention and control documents, we constructed a comprehensive failure system for a model that identifies the potential risks for nosocomial COVID-19 infection in the hemodialysis room. Subsequently, a thorough risk assessment of the potential failure factors identified in our model was conducted. The failure key factors corresponding to the human element in medical waste (garbage) disposal (C2) are verified to be the highest risk factors. They are as follows: The cleaning staff did not dispose of different types of medical waste (garbage) (C21), did not wear masks according to the regulations (C22), and lacked knowledge and norms of nosocomial IPC (C23). This study provides valuable insights for hospital decision-makers on the potential failure factors related to COVID-19 infections in hemodialysis rooms. By working with hospital infection specialists, the suggested improvement measures can help reduce the risk of virus exposure among hospital medical staff, patients, and cleaning staff.

Assessing evidence-based practice competencies of undergraduate nursing students using a developed multi-criteria decision-analysis model.

AIM: The developed multi-criteria decision analysis model was used to identify the inter-influence relationships and key factors affecting the EBP competencies of UNSs, to assess the EBP competencies of UNSs and based on these results, to formulate an improvement strategy to enhance the EBP competencies of UNSs. BACKGROUND: EBP is considered a core competency in international nursing practice. However, few studies have developed EBP evaluation models and applied them to assessing and improving the EBP competencies of UNSs. DESIGN: This is a quantitative study with multi-criteria decision-analysis model. METHODS: Firstly, the questionnaire was designed based on the characteristics of the DEMATEL and VIKOR-AS methods, which was completed by 17 nursing experts from a case hospital in Zhejiang Province, China. Subsequently, the DEMATEL method was used to analyze the inter-influence relationships among various criteria to determine their respective weights. Finally, the VIKOR method is utilized to integrate multiple criteria and their relative weights to assign comprehensive scores to each UNSs. RESULTS: The use of the DEMATEL method reveals that "Knowledge (C1)", "Mastering the basic scientific research methods during the study of the undergraduate courses (C11)", "Being able to consult clinical experts appropriately when encountering problems in clinical practice (C23)" and "Understanding the importance of reading journals related to the nursing profession regularly (C34)" were critical influencing factors. "Skill (C2)," "Being able to explain the essential roles of the best research evidence in determining clinical practice (C15)," "Being able to apply the collected research evidence to the individual case in nursing care (C25)" and "Paying attention to using the evidence-based nursing practice concept to determine the best clinical practice (C35)" were the most influential factors. According to the VIKOR method, the performance of the UNSs in the case hospitals in terms of EBP competencies from highest to lowest was Student C, Student B and Student A. However, all of these students suffered from deficiencies at the knowledge level. CONCLUSIONS: The application of the DEMATEL and VIKOR methods provides a systematic and comprehensive approach to the assessment of EBP competencies of UNSs. The lack of EBP competencies of UNSs in case hospitals is mainly reflected in knowledge level. To improve UNSs' EBP competencies, medical schools and hospital educators should propose short- and long-term strategies to improve knowledge.

Identification of key potential infection processes and risk factors in the computed tomography examination process by FMEA method under COVID-19.

PURPOSE: To identify the key infection processes and risk factors in Computed Tomography (CT) examination process within the standard prevention and control measures for the COVID-19 epidemic, aiming to mitigate cross-infection occurrences in the hospital. METHOD: The case hospital has assembled a team of 30 experts specialized in CT examination. Based on the CT examination process, the potential failure modes were assessed from the perspective of severity (S), occurrence probability (O), and detectability (D); they were then combined with corresponding risk prevention measures. Finally, key infection processes and risk factors were identified according to the risk priority number (RPN) and expert analysis. RESULTS: Through the application of RPN and further analysis, four key potential infection processes were identified, including "CT request form (A1)," "during the scan of CT patient (B2)," "CT room and objects disposal (C2)," and "medical waste (garbage) disposal (C3)". In addition, eight key risk factors were also identified, including "cleaning personnel does not wear masks normatively (C32)," "nurse does not select the vein well, resulting in extravasation of the peripheral vein for enhanced CT (B25)," "patient cannot find the CT room (A13)," "patient has obtained a CT request form but does not know the procedure (A12)," "patient is too unwell to continue with the CT scan (B24)," "auxiliary staff (or technician) does not have a good grasp of the sterilization and disinfection standards (C21)," "auxiliary staff (or technician) does not sterilize the CT machine thoroughly (C22)," and "cleaning personnel lacks of knowledge of COVID-19 prevention and control (C33)". CONCLUSION: Hospitals can publicize the precautions regarding CT examination through various channels, reducing the incidence of CT examination failure. Hospitals' cleaning services are usually outsourced, and the educational background of the staff employed in these services is generally not high. Therefore, during training and communication, it is more necessary to provide a series of scope and training programs that are aligned with their understanding level. The model developed in this study effectively identifies the key infection prevention process and critical risk factors, enhancing the safety of medical staff and patients. This has significant research implications for the potential epidemic of major infectious diseases.

Application of failure mode and effect analysis in ICU admission of potentially COVID-19 infected patients.

BACKGROUND: To analyze the admission and treatment process of potentially COVID-19-infected patients in the intensive care unit under normalization, prevention, and control of the pandemic. METHODS: A multidisciplinary team was assembled to develop a flowchart of potentially COVID-19-infected patients admitted to the intensive care unit and identify potential failure steps and modes throughout the process using the failure mode and effect analysis method. Through risk priority number (RPN) analysis of each failure mode, those with the highest impact on nosocomial infection were identified, and the priority of implementation was determined. Related corrective measures have been developed to continuously improve clinical practice and management. RESULTS: Eighty potential failure modes were identified, and 8 potential failure modes were identified with RPNs greater than 100. These high RPNs of the failure modes were associated with careless inquiries of epidemiological histories by nurses, inadequate implementation of management standards by nursing assistants, and exposure of attending physicians to potentially risky environments. Finally, 18 general corrective measures are proposed. CONCLUSIONS: Application of the failure mode and effect analysis method for quality improvement is a powerful tool for predicting potential failures in the process and can suggest corrective measures that could help avoid nosocomial infection during a pandemic.

Evaluation and improvement of workplace vertical violence of nursing interns based on the Importance-Performance Analysis method.

Purpose: To analyze the key factors related to workplace vertical violence among nursing interns in China and to propose strategies to improve the nursing practice environment. Methods: A cross-sectional study was conducted using the Importance-Performance Analysis (IPA) method to analyze the key factors and significance of workplace vertical violence for nursing interns. The data were obtained by administering a workplace vertical violence survey, designed specifically for this study, to 120 nursing interns at a tertiary general hospital in Zhejiang Province, China. Results: The results demonstrated that the variables "I was ordered to do something beyond my ability and lacked guidance (C3)," "Errors in work have been repeatedly emphasized, spread, or exaggerated (C8)," "I was unjustly criticized (C9)," "I was withheld or blocked information purposefully (C1)," and "I was belittled at work (C2)" were the most crucial variables for determining the presence of workplace vertical violence of nursing interns. Moreover, they are priority improvement variables. Conclusion: Managers must prioritize the use of relevant resources during internships to minimize false reinforcement and unfair criticism. Efforts should focus on improving information sharing, emphasizing the role of nursing interns in clinical work, providing better guidance when arranging for nursing interns to do work that exceeds their capacity, reducing workplace vertical violence, and improving nursing intern practice environments.

English training requirements and associated factors for non-native English-speaking nurses: A critical gap analysis based on the importance-performance method.

Aims and objectives: To investigate the English training requirements, priorities, and related factors of non-native English-speaking nurses. Background: Few studies have focused on the English training requirements of nurses in non-native English-speaking hospitals, and even fewer applied quantitative methods to analyze their English needs and related factors. Design: A total of 397 clinical nurses from a hospital in Zhejiang Province, China, were invited to answer questions from the 17-item English Language Requirement Scale (ELRS-17) through an online questionnaire system from May 7-12, 2021. Methods: The importance-performance analysis (IPA) method was used to identify the critical training requirement gaps in the English skills of non-native English-speaking nurses in the case hospital. Results: The results of requirements showed that looking up foreign literature, writing medical/nursing academic articles and reports, and attending international medical/nursing academic conferences were the top three English learning purposes for nurses. Critical gap analysis with the IPA method revealed that medical dialogues (e.g., morning shift conversations), speeches (e.g., academic symposia), and everyday talk (e.g., telephoning and greetings) are very important yet inadequately trained skills for nurses at present, while nurses are adequately competent at the important tasks of understanding medical/nursing lectures and courses and oral international academic reports and reading academic articles and reports. Conclusion: The results of this study indicate that English training requirements for non-native English-speaking nurses revolve around facilitating contribution to nursing research and conference attendance, while more focus on spoken English is needed. Hospital decision makers can better understand the requirements and current performance of English language training for non-native English-speaking nurses. Furthermore, a suitable training plan and corresponding content can be designed for nurses.

Identifying Key Factors for Burnout Among Orthopedic Surgeons Using the Analytic Hierarchy Process Method.

Objectives: To develop an evaluation model for, and identify key factors contributing to, burnout in orthopedic surgeons, providing a reference for the management of burnout among orthopedic surgeons in hospitals. Methods: We developed an analytic hierarchy process (AHP) model with 3 dimensions and 10 sub-criteria based on an extensive literature review and expert assessment. We used expert and purposive sampling and 17 orthopedic surgeons were selected as research subjects. The AHP process was then used to obtain the weights and to prioritize the dimensions and criteria for burnout in orthopedic surgeons. Results: The dimension of C 1 (personal/family) was the key factor affecting burnout in orthopedic surgeons, and in the sub-criteria, the top four sub-criteria were C 11 (little time for family), C 31 (anxiety about clinical competence), C 12 (work-family conflict), and C 22 (heavy work load). Conclusion: This model was effective in analyzing the key factors contributing to job burnout risk, and the results can inform improved management of the levels of burnout affecting orthopedic surgeons in hospitals.

Identification of critical quality factors and critical satisfaction gaps in emergency training courses for new nurses by the multi-criteria network structure model.

OBJECTIVE: To identify critical quality factors and critical satisfaction gaps in emergency training courses for new nurses through a systematic decision-making model. METHODS: Firstly, the service quality (SERVQUAL) was used in the evaluation index system of this study. Then, the decision-making trial and evaluation laboratory (DEMATEL) method was used to analyze the relationship structure and the corresponding weights between the indicators. Finally, the importance-performance analysis (IPA) method was used to identify the categories of all indicators and the corresponding strategic directions. Fifteen new nurses in Taizhou Hospital of Zhejiang Province were selected as participants in this study. RESULTS: The IPA results showed that "(C13)," "(C22)," "(C52)," "(C53)," "(C54)," "(C55)," "(C56),"and "(C57)" are critical satisfaction gaps. From the results of influence network and weight, empathy (C5) was the critical quality factor of the entire training course. The influence network relationship structure and weight had a 98.1% significant confidence level, indicating good stability. CONCLUSION: Teachers' empathy is key to the learning outcomes of new nurses in emergency nursing training courses. Hence, teachers should be attentive to the empathetic quality of their teaching methods to help new nurses gain knowledge and experience in emergency care, especially when they come from different professions and departments.

Applying a multi-criteria decision-making approach to identify key satisfaction gaps in hospital nurses' work environment.

Aim: A decision analysis model was constructed to explore the key factors affecting the job satisfaction of hospital nurses and to analyze the key satisfaction gaps in the case hospital. Background: In China, medical institutions are facing greater pressure and challenges in the normalization of epidemic prevention and control. Nurses play a critical role in the delivery of medical care services. Past studies have shown that improving job satisfaction among hospital nurses is important for both reducing nurse turnover and improving the quality of care. Methods: McCloskey/Mueller satisfaction scale (MMSS-31) was used to survey 25 nursing specialists in a case hospital in Zhejiang. Then, the Consistent Fuzzy Preference Relation (CFPR) method was used to analyze the degree of importance of dimensions and corresponding sub-criteria. Finally, the importance-performance analysis method was applied to identify critical satisfaction gaps for the case hospital. Results: In terms of local weight for dimensions, "Control/Responsibility (C 8)" ≻ "Praise/Recognition (C 7)" ≻ "Extrinsic Rewards (C 1)" are the top three key factors for nurses' work environment satisfaction in the case of a hospital. In addition, the sub-criteria "Salary (C 11)", "Benefits (C 13)", "Child care (C 33)", "Recognition-peers (C 73)", "Encouragement/feedback (C 74)", and "Decision making (C 85)" are the key factors for improving clinical nursing satisfaction in the case hospital. Conclusion: The issues that nurses care about but for which they have not attained expectations mainly involved extrinsic rewards, recognition/encouragement and control over their working process. The findings of this study could offer an academic reference for management and remind them to consider the above factors in exploring future reform, further improving nurses' job satisfaction and motivating them to provide better nursing services.

Using hybrid consistent fuzzy preference relations-importance-performance analysis model to improve shared decision-making quality based on orthopaedic nurses' perceptions.

PURPOSE: To understand key factors for shared decision-making (SDM) and the quality improvement of nursing decisions in the orthopaedic clinical environment. METHOD: This study applied the consistent consistent fuzzy preference relations (CFPRs) and importance-performance analysis (IPA) methods to explore the attribute weights and SDM performance, respectively. The dataset was collected from 16 orthopaedic clinical nurses' experiences in a third-grade and first-level general hospital in Taizhou, China. This study was performed according to the STrengthening the Reporting of OBservational studies in Epidemiology (STROBE) guidelines. RESULTS: The results showed that "I made clear to my patient or patient's family that a nursing care decision needs to be made", "I explained the advantages and disadvantages of the nursing care options to my patient or patient's family" and "I told my patient or patient's family that there are different nursing care options for caring his/her medical condition" were key factors for affecting SDM. The statistical significance confidence and difference error of weight results were 98.321% and 1.679%, respectively. In addition, "I asked my patient or patient's family which nursing care option he/she prefers" was the key factor for improving orthopaedic clinical nursing in the case hospital. CONCLUSION: The hybrid CFPRs-IPA model can help hospital managers effectively understand the key factors of SDM quality and improve the orthopaedic clinical nursing performance from nurses' perspectives. RELEVANCE TO CLINICAL PRACTICE: A quantitative decision-making model can help nurses understand the key factors affecting the quality of SDM in nursing decision-making and promote nursing decision-making and patient-centred nursing service quality. A series of corresponding SDM training courses (i.e. concepts, knowledge and skills) can be provided for hospital and nursing department managers to maximise the potentially available resources. PATIENT OR PUBLIC CONTRIBUTION: The clinical care process should be committed to involving patients in their care decisions and also provide an opportunity for patients to gain a comprehensive understanding of the care decision-making process in order to inform future patient contributions to care decisions.

Patient allocation method in major epidemics under the situation of hierarchical diagnosis and treatment.

OBJECTIVES: Patients are classified according to the severity of their condition and graded according to the diagnosis and treatment capacity of medical institutions. This study aims to correctly assign patients to medical institutions for treatment and develop patient allocation and medical resource expansion schemes among hospitals in the medical network. METHODS: Illness severity, hospital level, allocation matching benefit, distance traveled, and emergency medical resource fairness were considered. A multi-objective planning method was used to construct a patient allocation model during major epidemics. A simulation study was carried out in two scenarios to test the proposed method. RESULTS: (1) The single-objective model obtains an unbalanced solution in contrast to the multi-objective model. The proposed model considers multi-objective problems and balances the degree of patient allocation matching, distance traveled, and fairness. (2) The non-hierarchical model has crowded resources, and the hierarchical model assigns patients to matched medical institutions. (3) In the "demand exceeds supply" situation, the patient allocation model identified additional resources needed by each hospital. CONCLUSION: Results verify the maneuverability and effectiveness of the proposed model. It can generate schemes for specific patient allocation and medical resource amplification and can serve as a quantitative decision-making tool in the context of major epidemics.

The Hybrid Multiple-Criteria Decision-Making Model for Home Healthcare Nurses' Job Satisfaction Evaluation and Improvement.

Objectives: To investigate and evaluate the key factors related to job satisfaction performance of home healthcare nurses (HHNs). Methods: A total of 31 HHNs from three community hospitals in Zhejiang province were invited to participate in the study. They completed a questionnaire survey based on the home healthcare nurse job satisfaction scale (HHNJS) from February to March 2022. Consistent fuzzy preference relation (CFPR) methods and important-performance analysis (IPA) were used to obtain the attribute weights and performance for HHNs job satisfaction. Results: The results showed that the attributes of C 13, C 14, C 15, C 23, C 24, C 42, C 51, and C 52 were key factors influencing HHNs job satisfaction. Conclusion: The hybrid multiple-criteria decision-making (MCDM) model can help home-healthcare-agency administrators better understand the key factors related to HHNs job satisfaction and establish reasonable improvement strategies.